Method of evaluating change in energy consumption due to volt var optimization

ABSTRACT

A method of evaluating an optimization system is disclosed. The system is transitioned from an on state to an off state. Data is collected at time intervals for a time period before and after the system is transitioned from the on state to the off state. The transitioning occurs while a load of a particular type is active. In one embodiment, the optimization system is a Volt/VAR Optimization (VVO) system.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. non-provisional applicationSer. No. 14/870,525, filed Sep. 30, 2015, which claims the benefit ofU.S. provisional application 62/057,505, filed Sep. 30, 2014, titled“Development of Method for Evaluating Benefits of Volt VAR Control andVerification,” hereby incorporated by reference in its entirety for allof its teachings.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under ContractDE-AC0576RL01830 awarded by the U.S. Department of Energy. TheGovernment has certain rights in the invention.

TECHNICAL FIELD

This invention relates to Volt/VAR Optimization (VVO) systems. Morespecifically, this invention relates to a more efficient method ofevaluating the effectiveness of a VVO system by using the change inactive power demand through a small number of transitions from a VVO-onstate to a VVO-off state.

BACKGROUND

Volt/VAR Optimization (VVO) is a utility-centric technology that focuseson the coordinated control of tap changers, voltage regulators, andshunt capacitors to achieve a global objective or objectives. The mostcommon global objectives are the reduction of end-use energy and theregulation of power factor to a specified value. To achieve these goals,a general VVO system uses a combination of Conservation VoltageReduction (CVR), which is achieved through the control of tap changersand voltage regulators, and power factor control, which is achievedthrough the control of shunt capacitors. When properly implemented,these systems will provide end-use customers with the same quality ofservice while reducing annual energy consumption. An increase in theefficiency of the system can also be achieved via reduced system losses,but it is a small effect compared to reductions at the end-use. The endresult of a properly operated VVO system is lower energy usage and amore efficient system. Others systems may take a simpler approach ofimplementing CVR alone.

A VVO system has two main functional components. The first, and primary,function is the coordination of tap changers and voltage regulators, atthe feeder level, to reduce energy consumption. The second function isthe coordination of capacitors with a weighted dual objective of voltageflattening and power factor correction. In this system, the weighting ofthe voltage flattening is slightly higher than the weighting for powerfactor optimization.

One challenge that utilities face with VVO is verifying/validating theeffectiveness of the system to their regulating authority. Thevalidation of performance is generally achieved with a 60 or 90 dayon/off evaluation process which requires the VVO system to be turned onor turned off on alternate days for the 60 or 90 day period, and isexpensive and complicated. The 60 or 90 days evaluation period isrequired because of VVOs interaction with end-use loads that havethermal control loops, e.g. heating and cooling.

Generally outside firms are hired by utilities to conduct theevaluations, and execute the analysis. Commonly used VVO analysisprotocol requires the VVO system to be turned on and off on alternatedays for 90 days. Thus, during half of the evaluation process the systemis off for testing purposes, representing a loss of benefits. The activepower demand is adjusted to control for factors that affect the demandsuch as temperature, day of week, time of day, and on-days and off-daysare compared to estimate the energy reduction achieved by the VVOsystem. Large amounts of data must be collected, and the analysisrequires temperature correction of active power demand. As VVOdeployments becomes more common and new installations requireevaluation, the development of a simpler method, which requires ashorter period of data collection, to benchmark new evaluations wouldsave time and money.

SUMMARY

The present invention is directed to a method of evaluating anoptimization system. The method includes transitioning the system froman on state to an off state; and collecting data at time intervals for atime period before and after the system is transitioned from the onstate to the off state.

In one embodiment, the transitioning is performed at least twice a dayand completed in approximately 5 to 15 minutes. The data may becollected at, but not limited to, 10 to 60 second time intervals.

The method may further include applying a filter to smooth the data.

In one embodiment, the optimization system is a Volt/VAR Optimization(VVO) system, and the VVO system includes a conservation voltagereduction (CVR) system. In another embodiment, the optimization systemis a CVR alone. Other optimization systems may be used with methods ofthe Present Invention.

The evaluation may be carried out over multiple weeks, but other timeranges for evaluation purposes are possible.

In another embodiment of the present invention, a method of evaluatingthe change in energy consumption due to the action of a VVO system isdisclosed. The method includes transitioning the system from an on stateto an off state. The method also includes collecting data at timeintervals for a time period before and after the system is transitionedfrom the on state to the off state, wherein the transitioning occurswhile a load of a particular type is active.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows power demand and voltage for a single on-off transition ona feeder with a VVO system, an example when the change in power demandin a single transition is larger than the ambient level of noise.

FIG. 2 shows power demand and voltage for a single on-off transition ona feeder with a VVO system, an example when the change in power demandin a single transition is not larger than the ambient level of noise.

FIG. 3 shows power demand through on-off transition for 22 days on afeeder with a VVO system.

FIG. 4 shows average power demand through on→off transition and bumppoints on a feeder with a VVO system.

FIG. 5 shows variation in bump estimate with number of days averaged ona feeder with a VVO system.

FIG. 6 shows variation in standard deviation with number of daysaveraged on a feeder with a VVO system.

FIG. 7 shows variation in bump estimate with number of days averaged forthe aggregated load of 13 feeders with a VVO system.

FIG. 8 shows variation in standard deviation of bump calculations withnumber of days averaged for individual feeders, an aggregate of threefeeders, and an aggregate of 13 feeders, with a VVO system.

FIG. 9 shows an idealized daily load shape, with the time of day of bumptests marked as shown at approximately 4:00 and 17:00.

FIG. 10 shows an actual average load shape for a feeder with a VVOsystem, with time of day of bump tests marked as shown at approximately4:00 and 17:00.

FIG. 11 shows the average daily load shape for a feeder with a VVOsystem, with time of day of bump tests marked as shown at approximately4:00 and 17:00.

FIG. 12A shows the estimated energy reduction in absolute energy due tothe VVO system using a bump test calculation considering a morning bumponly and an evening bump only.

FIG. 12B shows the estimated energy reduction by percentage change dueto the VVO system using a bump test calculation considering a morningbump only and an evening bump only.

FIG. 13 shows ambient temperature during the evaluation period usingconventional day-on/day-off method and the evaluation period using thebump test method of the present invention.

FIG. 14 shows total load during the evaluation period using theconventional day-on/day-off method and the evaluation period using thebump test method of the present invention.

FIG. 15A shows the results of a bump test method of the presentinvention compared to the conventional day-on/day-off method. The changein energy consumption in absolute energy is calculated for thirteendistribution feeders with a VVO system.

FIG. 15B shows the results of a bump test method of the presentinvention compared to the conventional day-on/day-off method. The changein energy consumption in percent change is calculated for thirteendistribution feeders with a VVO system.

FIG. 16A compares the average energy reduction results in absoluteenergy of the conventional day-on/day-off calculation to the bump testmethod of the present invention, for the aggregate load of eachsubstation bus with a VVO system.

FIG. 16B compares the average energy reduction results in percent changeof the conventional day-on/day-off calculation to the bump test methodof the present invention, for the aggregate load of each substation buswith a VVO system.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description includes the preferred best mode ofembodiments of the present invention. It will be clear from thisdescription of the invention that the invention is not limited to theseillustrated embodiments but that the invention also includes a varietyof modifications and embodiments thereto. Therefore the presentdescription should be seen as illustrative and not limiting. While theinvention is susceptible of various modifications and alternativeconstructions, it should be understood, that there is no intention tolimit the invention to the specific form disclosed, but, on thecontrary, the invention is to cover all modifications, alternativeconstructions, and equivalents falling within the spirit and scope ofthe invention as defined in the claims.

The present invention includes methods and systems that allow utilitiesto perform Volt/VAR Optimization evaluation in a shorter time scale andin-house, compared to existing evaluation processes, thus reducing costsand time consumption.

The methods disclosed herein effectively reduce the evaluation time, andallow for the possibility of a continuous commission system. The abilityto integrate the solution into a continuous evaluation/commissioningscheme is a major improvement over existing evaluation methods. Thiscapability would be of extreme value during rate filing discussions withregulatory authorities.

The methods of the present invention take less time than currentlycommon evaluation methods and systems. Second, because of the shortduration of the transition, the load composition can be assumed to beapproximately constant throughout the transition period, and it does notrequire a complex temperature correction, making the evaluation methodsof the present invention suitable for integration into an automatedprocess embedded in a commercially available control system.

The present invention uses the change in active power demand at thepoint of a transition from VVO-on state to VVO-off state to evaluate theenergy reduction capability of the system, which includes calculatingthe change in energy consumption due to the operation of the VVO system.

The evaluation method uses only data from a brief time periodsurrounding each “bump” or transition from a VVO “on” state to a VVO“off” state. In some VVO systems, the transition may complete rapidlyenough that data from, say, approximately 5 minutes before the bump to,say, approximately 10 minutes after the bump may be sufficient. Becauseof the shorter time period involved under the methods of the presentinvention, there is no need or requirement to temperature correct thedata from the bump test.

In one embodiment, the method of evaluating an optimization system, suchas a VVO system, includes transitioning the system from on state to anoff state and collecting data at time intervals for a time period beforeand after the system is transitioned from the on state to the off state.The evaluation may be carried out over multiple days or multiple weeks.

The transitioning may be performed once a day or at least twice a dayand completed in a matter of seconds, minutes, or hours. In oneparticular embodiment, the transitioning is completed in approximately 5to 15 minutes, but is not meant to be limiting.

The data may be collected at various time intervals. In one particularembodiment, the data is collected in 10 to 60 second time intervals. Afilter may be applied to smooth the data.

In one particular embodiment, an on-off transition is performed byswitching off the VVO system and allowing voltage control setpoints toreturn to their default levels, resulting in a sudden increase involtage throughout a distribution feeder. The voltage at a substationbus stabilizes at the higher level within two minutes of the initiationof the transition. An analysis of voltage measurements at certainend-of-line (EOL) points showed that the transition to the highervoltage level was complete in a matter of a few minutes throughout thelength of each feeder.

EXPERIMENTAL SECTION

The following examples from a study serve to illustrate embodiments andaspects of the present invention and are not meant to be construed aslimiting the scope thereof.

Example

Energy Reduction Evaluated with Bump Test Method

This Section describes the bump test method of the present invention toevaluate end-use energy reductions. The data set and the bump testanalysis methodology are described. Next, the overall end-use energyreduction in the VVO system, as computed by the bump test method, iscompared to the energy reduction calculated from the conventional orprior day-on/day-off evaluation.

Data Collected

The data required to conduct a bump test was collected from Nov. 4, 2013through Nov. 25, 2013. To conduct the analysis, the electric utilityprovided time-series Supervisory Control And Data Acquisition (SCADA)data recorded at 10-second intervals for the following quantities, allindividual phase measurements:

-   -   Active power (MW) and reactive power (MVAR) demand of the feeder    -   Voltage magnitude at the substation bus    -   The active and reactive power flow through and voltage at both        sides of any mid-line regulators    -   The voltage at every capacitor and the active and reactive power        flow through the line at the connection point    -   The active and reactive power flow through each switch and the        voltage at both sides    -   The voltage at End-of-Line (EOL) points

The bump test evaluation requires only data from a brief time periodsurrounding each bump. For this system, the transition completed rapidlyenough that data from 5 minutes before the bump to 10 minutes after thebump was sufficient, although other time ranges may be used. Because ofthe brief time period involved there is no need to temperature correctdata from a bump test.

Bump Test Methodology

The following sections describe the bump test method used in this studyto calculate the change in energy consumption due to the operation ofthe VVO system. Data quality and data quantity are discussed.

Carrying Out and Analyzing a Bump Test at Single Point in Time

An on→off transition is performed by switching off the VVO system andallowing voltage control setpoints to return to their default levels,resulting in a sudden increase in voltage throughout the feeder. Thevoltage at the substation bus stabilizes at the higher level within twominutes of the initiation of the transition. An analysis of voltagemeasurements at EOL points showed that the transition to the highervoltage level was complete in less than five minutes throughout thelength of each feeder. This rapid increase in voltage results in a stepchange increase in energy.

FIG. 1 shows an example of an on→off transition on feeder OW3 of the VVOsystem. The voltage at the substation bus (scaled to a 120V base) can beseen as labeled on the right-hand axis, and the active power demand canbe seen as labeled on the left-hand axis. The multi-volt rise, due toregulator tap operations, at the transition can be clearly seen, and theresponding increase in active power demand is also clearly evident, forthis particular transition. The change in energy consumption thataccompanies the change in voltage forms the basis for the bump testevaluation methodology.

Not all transitions are as easy to characterize as the transition shownin FIG. 1. FIG. 2 shows a transition on the same feeder, at the sametime of day, with the voltage and active power demand. For thisparticular transition, the transition is not clear and easy todistinguish from the minute-to-minute random variations of demand. Onsome days on some feeders, a step change in active power demand wasclearly evident at the transition point, but for others, it could not bereliably calculated.

FIG. 3 shows the active power demand for individual days, as measured atthe head of feeder OW3 through the 4:00 am transition time. There are 22transitions at this time. The data is shown for an hour centered aboutthe on→off transition. For each individual day of data, the response dueto the VVO system transition is not significantly larger than the randomvariations in active power demand, and an energy-reduction estimatecannot be reliably calculated directly from a single day.

In order to distinguish the step change at the transition from therandom variation in demand, the active power demand at a given time isaveraged over all 22 days in the study period and filtered. Onlytransitions that occurred at the same time of day were combined into asingle calculation; transitions that occurred at different times of daywere not averaged together. The result is the thicker, black line inFIG. 4. For each of the feeders studied, the average of 22 days shows aclear step change at the transition time, and a change in power demanddue to the transition can be clearly identified. The active power demandat 4:00 is marked with an asterisk, and the active power demandpost-transition is marked as well with an asterisk. The active powerdemand post-transition was identified as the demand at the first localmaximum after the transition time. The difference between the two is theaverage change in active power demand due to the operation of the VVOsystem at the transition time.

For this study, all data was recorded at 10-second intervals. To furtherimprove the signal-to-noise ratio, a Savitzky-Golay filter was appliedto the active power demand. A Savitzky-Golay filter is a peak-preservingfilter, a generalized moving average with filter coefficients determinedby an unweighted linear least-squares regression and a polynomial model.A polynomial of order 2 and a span of the moving average to 7 datapoints were used. The span was chosen because a width of 30 secondsreduced random variations without depressing the peak of the bump. Theorder of the polynomial was chosen because it smoothly interpolatedthrough the small number of data points in each sample set. The smoothedactive power demand is shown in the thicker, black line. Note that sincethe bump test response is complete in less than five minutes, thisfiltering step would not be possible without high time resolution data,as it requires that multiple timesteps of data are recorded through thebrief transition period.

Effect of Study Timespan on Bump Test Results

This study was carried out over 22 days and all of the data combinedinto a single result. It is of interest to determine if the full 22 dayswere necessary, or if similar results could be obtained from a smallerset of days. While the error on the estimate from the collective 22 daysis difficult to estimate, the error on the estimate from smaller subsetsof days can be calculated, and then the results extrapolated for a22-day sample.

Random subsets of the 22 days were taken, for sample sizes ranging from3 days to 15 days. The energy reduction calculation was carried out oneach randomly sampled subset. This was repeated for 10 different randomsamples of a given size, and a standard deviation is calculated from theset of 10. That entire process was then carried out 10 times. Thestandard deviation of the energy reduction calculation can be computedfor each different set of random samples. In addition, since the processis repeated, the standard deviation of that standard deviation can becalculated across the entire set of samples. Statistics can be developedfor how results of the bump test calculation and the standard deviationof the bump test calculation trend as a result of the number of daysconsidered in the calculation. FIG. 5 shows an example of a set ofcalculations carried out for sample sizes ranging from 3 days to 15days, for feeder OW3. The round circles are the average percentagechange in active power demand from the calculation, for each set ofrandomly sampled subsets. The “x” marks indicate the extent of thestandard deviation of each subset. Results are shown for the morningbump of feeder OW3; results were similar for other feeders.

The average standard deviation of the calculated result is plotted as afunction of the number of days in the subset in FIG. 6. It can be seenthat the standard deviation of the percentage change in active powerdrops significantly as the number of days in the subset increases from 3days to 7 days, and then continues to decline slowly as the number ofdays in the subset increases further. The average standard deviationshrinks to 0.5% with 11 days in the sample subset. Results are shown forthe morning bump of feeder OW3; results were similar for other feeders.In general, a bump test span of two weeks seems to be sufficient tobring the standard deviation of the calculated percentage active powerreduction below 0.5%.

This section has described how the number of days in the sample affectsthe error on the result for a single feeder. The next section describeshow that changes when load is aggregated from multiple feeders.

Effect of Load Aggregation on Bump Test Results

As seen in FIG. 1 and FIG. 2, the random variation in power demand fromone timestep to the next can be a significant fraction of the size ofthe step change in demand due to the transition of the VVO state. Oneway to minimize the effect of that random variation on the result is toaverage across many days, as described in the previous section. Adifferent way is to aggregate additional load, so that the randomvariations are a smaller fraction of the total load and the total stepsize.

Instead of looking at an individual feeder, the total demand on asubstation bus, or the total demand of the entire system under study,can be aggregated and the same calculation carried out as described inthe previous section. If that aggregation is performed, the number ofdays required to reach the same level of uncertainty is reduced.

FIG. 7 shows the same calculation as shown in FIG. 5, but carried out onthe aggregated demand of the entire system under study, the sum ofdemand from all 13 feeders. Note that the limits on the y axis are thesame on the two figures. It can be seen that the variation in the resultcalculated from randomly chosen subsets of days is smaller for the bustotal than the individual feeder, and declines more quickly as thenumber of days increases.

The effect of the load aggregation can be seen by comparing the averageof the standard deviation of the calculation from the randomly sampledsubsets—the same calculation shown in FIG. 6—for individual feeders, forthe aggregate demand on a substation, and for the aggregate demand onthe system as a whole. This is shown in FIG. 8. FIG. 8 shows thecalculations for OW1, OW3 and OW5, which are the individual feeders ofthe 88^(th) substation, along with the aggregate of all three—the demandon the 88^(th) substation as a whole. Also shown in FIG. 8 is theaggregate of the entire system, the sum of all 13 feeders on the threesubstations. The effect of further load aggregation can be clearly seen.This suggests that for an estimate of a target uncertainty, the numberof days that is required to average decreases as the load aggregationincreases. If the goal is, for example, to achieve an estimate of theeffectiveness of the VVO system that is accurate to within ±0.5%, thenumber of days that is required to average is two weeks or more for anestimate of an individual feeder's performance, roughly a week for asubstation, and perhaps as little as four days for a set of substations.

Previous sections have described how to calculate active power reductionat a single point in time and how error can be estimated. The nextsection describes how to extrapolate from those results to an estimateof the total energy reduction over the course of a day.

Extrapolating Bump Tests to Energy Reduction Estimate

The step change in energy as a response to the step change in voltagecan be used to calculate the instantaneous end-use energy reduction atthe point in time of the on→off transition. However, the desired valueis the end-use energy reduction, for an entire day, and over an entireyear. Since load varies over the course of a day, as does theeffectiveness of the VVO system, the bump test may be carried outmultiple times per day and the results extrapolated into an estimate forthe day. Due to variation over the course of the day, the calculationmay increase in accuracy if more times of day were tested. The desire toincrease accuracy should be balanced against both the need to shieldcustomers from excessive changes in voltage and to minimize the impacton tap changing and switching equipment. While the voltage remainswithin the acceptable bands specified by ANSI Standard C84.1 both beforeand after the transition, repeated, significant change in voltage maycause adverse impacts on some customer applications. During thisevaluation, these conflicting needs were considered and it was decidedthat, for this example study, bump tests would be carried out twice perday, once near system minimum load and once again near system peak load,as a way to more efficiently capture maximally different loadcompositions. It should be noted, of course, that the bump test may becarried out more than twice per day or less than twice per day. FIG. 9shows an idealized picture of a daily load shape. The system minimum andmaximum are marked on the curve. For the system in the test footprint,those times (shown on the curve as marks) were 4:00 and 17:00.

FIG. 10 shows an actual average load shape, from feeder OW3. It can beseen that for this feeder, the chosen times did not capture the time ofmaximum load. Because the time of day of peak load varied betweenfeeders, the maximum load was not effectively captured by the 17:00 bumpfor many of the feeders in this study. For this particular feeder, theload shape suggests that a more accurate estimate of overall energysavings might be achieved by performing more bumps over the course ofthe day, such as three bumps: at middle-of-the night minimum load, atthe middle of the day intermediate loading levels, and in the earlyevening at the peak load time period.

For one feeder in particular, ZN4, the selected times clearly did not doan adequate job of capturing the effect of the VVO system over thecourse of the day. The average load over the course of the day is shownin FIG. 11. Feeder ZN4 hosts an industrial load of ˜800 kW, a rockcrusher, which turns on each weekday at 6:00 and turns off at 16:00.Results from the conventional day-on/day-off study indicate that theportion of the feeder where the rock crusher is connected shows almostno change in energy consumption at all due to the VVO system. Giventhose results and the time of day of the bump tests, it is expected thatthe estimate of energy reduction from the bump test would over-estimatethe energy reduction as compared to the day-on/day-off calculation. Aswill be seen and described later below, this is consistent with what isobserved.

The extent to which variation due to differences in load compositionaffects the calculation of overall energy savings can be inferred bycomparing energy reduction calculated from the morning bumps alone (bumptests carried out at 4:00) to the energy reduction calculated from theevening bumps alone (bump tests carried out at 17:00). FIGS. 12A and 12Bshow the estimated energy reduction due to the VVO system, with FIG. 12Ashowing the estimated energy reduction in absolute energy and FIG. 12Bshowing the estimated energy reduction in percentage change. The resultsfrom considering the morning bumps only and extrapolating over theentire day are compared next to the results when considering eveningbumps only. The extrapolation was carried out by calculating theinstantaneous reduction in active power demand at the time the bump testwas carried out, and then scaling that instantaneous reduction by theratio of the average active power demand over the course of the day tothe active power demand at the time of the bump. For example, toextrapolate the morning bump value to an estimate of the total energyreduction,

$\begin{matrix}{{\Delta \; E_{total}} = {\Delta \; {E_{am} \cdot \frac{\overset{\_}{M\; W}}{M\; W_{am}}}}} & (2.1)\end{matrix}$

where:ΔE_(total): total daily reduction in energy consumption due to operationof VVO systemΔE_(am): reduction in energy consumption as calculated from the morningbump onlyMW: average active power demand over the entire dayMW_(am): active power demand at the time of the morning transition

From FIGS. 12A and 12B it can be seen that for most feeders there issignificant difference between the two estimates, and in roughly half ofcases, error bars do not overlap. This shows that if only a single bumptest is used, the estimated results may vary by as much as 2%, dependingon which time of day is chosen. Before carrying out an evaluation of theenergy reduction using bump tests, it is important to consider the dailyload profile of the system under study. More accurate results may beobtained if the time of day of the bump tests is distributed so as tocapture key features in the load profile, and then the individual bumptests are scaled appropriately in the full-day result. Some applicationof engineering judgment is required.

For this study, with two bump tests per day, the results from themorning and evening bumps were combined in a weighted average in orderto estimate the total energy reduction due to the VVO system over thecourse of the whole day. The calculated change in active power demand atthe time of each bump was weighted by relative load at the time of thetransition, in order to more heavily weight the results from times withmore load, since it will be a larger fraction of the day's total load.

$\begin{matrix}{{\Delta \; E_{total}} = {{\Delta \; {E_{am} \cdot \frac{M\; W_{{am}\;}}{{M\; W_{am}} + {M\; W_{p\; m}}}}} + {\Delta \; {E_{p\; m} \cdot \frac{M\; W_{p\; m}}{{M\; W_{{am}\;}} + {M\; W_{p\; m}}}}}}} & (2.2)\end{matrix}$

where:ΔE_(total): total daily reduction in energy consumption due to operationof VVO systemΔE_(am): reduction in energy consumption as calculated from the morningbump onlyΔE_(pm): reduction in energy consumption as calculated from the eveningbump onlyMW_(am): active power demand at the time of the morning transitionMW_(pm): active power demand at the time of the evening transition

The results of analysis using equation (2.2) are shown next and comparedto the results of the conventional day-on/day-off evaluation.

Change in End-Use Energy Consumption as Computed by Bump Test

The results of the bump test were compared against the results of theconventional day-on/day-off evaluation of the energy reduction. It isimportant to recognize, however, the difference in season between thetime the day-on/day-off evaluation was carried out and when the bumptest was carried out. As a result, the performance of the VVO system wasdifferent between day-on/day-off evaluation and the bump testevaluation. Because external air temperature has such as a strong impacton active power consumption, the differences in temperature for the twotime periods were examined. FIG. 13 shows time series data of ambienttemperature recorded during the two studies, with the averagetemperature observed during each study shown as a thicker line. Theday-on/day-off evaluation was carried out over 90 days between late Juneand early October, 2013. Daytime high temperatures routinely exceeded90° F. and the lowest temperature observed was above 40° F. It is highlylikely that air conditioning was a significant fraction of the loadduring much of this evaluation. In contrast, the bump test was carriedout over three weeks in mid-November, 2013, when temperatures weresignificantly cooler; the coldest temperature reached during the bumptest period was less than 20° F. and the daytime highs were typically40-70° F. It is not likely that air conditioning was a significantportion of the load during this evaluation. The difference in averagetemperature between the two evaluation periods was approximately 30° F.

Due to the difference in ambient temperature, the load level and loadcomposition were not the same during the two studies. FIG. 14 shows thecombined active power demand of the 13 feeders in the system, withaverage load level over the course of the two studies shown as a thickerline. Over the course of the day-on/day-off evaluation, the average loadon the entire system under study was 51.3 MW. The average load on theentire system under study over the course of the bump test evaluationwas only 31.3 MW.

The bump test methodology as described above was applied to the 22 daysof data. FIGS. 15A and 15B show the change in energy consumption for thethirteen distribution feeders, in both absolute energy values, FIG. 15A,and by percent, FIG. 15B. The circles indicate the change in energyconsumption and the horizontal bars the standard error on thecalculation. The energy reduction is calculated for all three phases inaggregate. The results from the day-on/day-off calculation are shown incomparison to the results from the bump test calculation.

Due to the significant difference in load level, it is expected that theaverage energy reduction on each feeder will not match between the twostudies. Calculations of percentage energy reduction, while they arelikely to be affected by difference in load composition, are more likelyto be comparable. It can be seen in FIGS. 15A and 15B that the energyreductions in MWh, FIG. 15A, do not agree well between the two studies,as expected; results from almost all feeders do not have overlappingerror bars. It can also be seen that the percentage energy reductions,FIG. 15B, do agree between the two methods, with the exception of feederZN4. As previously discussed, this is expected because the bump testtimes of day do not overlap with the time when a significant industrialload, which has little observed energy reduction response, is active.

The analysis indicated that the variation in the result decreased asload as aggregated across multiple feeders. The load was aggregated foreach of the five substation buses in the three substations in the areaunder study and the bump test calculation was carried out. In the sameformat as shown in FIGS. 15A and 15B, FIGS. 16A and 16B compare theresults of the day-on/day-off calculation to the results of the bumptest calculation, for the aggregate load of each substation bus.Substation bus labels used by the utility were adopted:

-   -   OWBUS1 includes feeders OW1, OW3, and 05    -   XGBUS1 includes feeders XG1 and XG3    -   XGBUS2 includes feeders XG2 and XG4    -   ZNBUSA includes feeders ZN1, ZN3, and ZN5    -   ZNBUSB includes feeders ZN2, ZN4, and ZN6

Similar to the feeder-level results shown in FIGS. 15A and 15B, theaverage energy reduction results in FIGS. 16A and 16B do not agreebetween the two analyses. Also similar to results shown in FIG. 15B, thepercentage energy reductions of FIG. 16B do match within error bars forthe two results. It can be seen that the calculated percentage energyreduction results from the two methods match slightly more closely whenthe load is aggregated across multiple feeders, and that the error barson both calculations are reduced. This indicates that more accurateresults for energy reduction can be achieved by aggregating largercollections of load before carrying out an analysis.

For the VVO system used in testing the performance of the method, thebump test, carried out using data from a three week evaluation period,effectively reproduces the percentage energy reduction results from theconventional 90-day day-on/day-off evaluation. Since this analysis hasshown that the bump test can effectively reproduce the percentage energyreduction, an accurate energy reduction in MWh could be computed bymultiplying the percentage energy reduction by the load level.

CONCLUSIONS FROM BUMP TEST EVALUATION

The methods of the present invention were developed to include bumptests to evaluate the change in end-use energy consumption due to theoperation of a VVO system. The evaluation of the percentage energyreduction due to the operation of the VVO system, using the bump testmethod described in the study, agree within error bars to the results ofthe lengthier and more complex, conventional day-on/day-off evaluation.

While a number of embodiments of the present invention have been shownand described, it will be apparent to those skilled in the art that manychanges and modifications may be made without departing from theinvention in its broader aspects. The appended claims, therefore, areintended to cover all such changes and modifications as they fall withinthe true spirit and scope of the invention.

1-16. (canceled)
 17. A method of evaluating a reduction in energy for aperiod due to a VOLT/VAR optimization (VVO) system that is disposed inan electrical grid, the VVO system using a coordination of tap changersand voltage regulators at a feeder level to reduce energy consumption,the method comprising: causing a transition of the VVO system from an onstate to an off state at least twice in a period; for each of thetransitions, performing operations comprising: receiving electrical gridcharacterization data corresponding to time periods before and after arespective transition of the VVO system; determining a change in activepower demand for the respective transition based on the electrical gridcharacterization data; and calculating a reduction in energy consumptionfor the respective transition based on the change in active power demandfor the respective transition; calculating the reduction in energy forthe period based on the reduction in energy consumption for each of thetransitions; and determining a performance of the VVO system in reducingenergy consumption based on the reduction in energy for the period. 18.The method of claim 17, wherein the electrical grid characterizationdata comprises active power (MW) and reactive power (MVAR) demand of afeeder, voltage magnitude at a substation bus, active and reactive powerflow through and voltage at both sides of any mid-line regulators,voltage at a capacitor, active and reactive power flow through a line ata connection point, active and reactive power flow through a switch andvoltage at both sides, or voltage at end-of-line (EOL) points.
 19. Themethod of claim 17, wherein the electrical grid characterization data iscollected at ten to sixty second time intervals.
 20. The method of claim17, further comprising, for each of the transitions, applying a filterto smooth the electrical grid characterization data.
 21. The method ofclaim 17, wherein the VVO system includes capacitors that are used toflatten a voltage and correct a power factor.
 22. The method of claim17, further comprising repeating the causing, the operations, thecalculating, and the determining the performance for a plurality ofperiods.
 23. The method of claim 22, wherein the reductions in energyfor the respective periods are aggregated to determine a total reductionin energy for the plurality of periods.
 24. The method of claim 17,wherein the method further comprises, for each of the transitions,responsive to the VVO system being off for a predetermined period oftime, transition the VVO system from the off state to the on state. 25.The method of claim 24, wherein the predetermined period of time isbetween five and fifteen minutes.
 26. The method of claim 17, whereinthe VVO system includes a Conservation Voltage Reduction (CVR) system.27. The method of claim 26, wherein the CVR system is used to controlthe tap changers and voltage regulators.
 28. A method of evaluating areduction in energy for a period due to a Volt/VAR optimization (VVO)system that is disposed in an electrical grid, the VVO system using acoordination of tap changers and voltage regulators at a feeder level toreduce energy consumption and a coordination of capacitors to flattenvoltage and correct a power factor, the method comprising: causing atransition of the VVO system from an on state to an off state at leasttwice in a cycle, the transitions based on a particular type ofelectrical load being active; for each of the transitions, performoperations comprising: receiving electrical grid characterization datacorresponding to time periods before and after a respective transitionof the VVO system; determining a change in active power demand for therespective transition based on the electrical grid characterizationdata; and calculating a reduction in energy consumption for therespective transition based on the change in active power demand for therespective transition; calculating the reduction in energy for the cyclebased on the reduction in energy consumption for each of thetransitions; and determining a performance of the VVO system in reducingenergy consumption based on the reduction in energy for the cycle. 29.The method of claim 28, wherein the electrical grid characterizationdata comprises active power (MW) and reactive power (MVAR) demand of afeeder, voltage magnitude at a substation bus, active and reactive powerflow through and voltage at both sides of any mid-line regulators,voltage at a capacitor, active and reactive power flow through a line ata connection point, active and reactive power flow through a switch andvoltage at both sides, or voltage at end-of-line (EOL) points.
 30. Themethod of claim 28, wherein the electrical grid characterization data iscollected at ten to sixty second time intervals.
 31. The method of claim28, further comprising, for each of the transitions, applying a filterto smooth the electrical grid characterization data.
 32. The method ofclaim 28, further comprising repeating the causing, the operations, thecalculating, and the determining the performance for a plurality ofcycles.
 33. The method of claim 32, wherein the reductions in energy forthe respective cycles are aggregated to determine a total reduction inenergy for the plurality of cycles.
 34. The method of claim 28, whereinthe method further comprises, for each of the transitions, responsive tothe VVO system being off for a predetermined period of time, transitionthe VVO system from the off state to the on state.
 35. The method ofclaim 34, wherein the predetermined period of time is between five andfifteen minutes.
 36. The method of claim 34, wherein the predeterminedperiod of time allows for a higher voltage level to stabilize at asubstation bus and for the higher voltage level to transition toend-of-line (EOL) points.